Mavri, Aekaterini, Ioannou, Andri and Loizides, Fernando ORCID: https://orcid.org/0000-0003-0531-6760 2019. On the reliability and factorial validity of the assessment scale for creative collaboration. Presented at: INTERACT 2019, Paphos, Cyprus, 2-6 Sep 2019. Published in: Lamas, David, Loizides, Fernando, Nacke, Lennart, Petrie, Helen, Winckler, Marco and Zaphiris, Panayiotis eds. Human-Computer Interaction: INTERACT 2019, Part I. Lecture Notes in Computer Science. Lecture Notes in Computer Science , vol.11746 Cham, Switzerland: Springer Verlag, pp. 783-792. 10.1007/978-3-030-29381-9_46 |
Abstract
Creativity, a primary objective across academic disciplines, has received considerable attention over the past few decades. While much focus has been put on the measurement of individual creativity, a notable research gap remains regarding social collaborative creativity that occurs in blended learning settings. This work offers an initial validation of the psychometric properties of a self-reported instrument, the Assessment Scale for Creative Collaboration (ASCC) that can measure learner perceptions of creative collaboration in a team within a computer-supported collaborative learning (CSCL) context. In this study, 236 undergraduate and graduate students rated the key variables of creative collaboration. Exploratory factor analysis resulted in a three-factor scale (21 items) measuring ‘Synergistic Social Collaboration’, ‘Distributed Creativity’ and ‘Learning Regulation and Achievement’. Cronbach’s alphas indicated good internal consistency for the subscales. An instrument with psychometric properties for the assessment of creative collaboration is much-needed for the growing community of researchers and practitioners looking into creativity in education. It is also critical in advanced technical subjects, such as Design, HCI and Engineering, where collaboration is essential in developing innovative products.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | Springer Verlag |
ISBN: | 978-3-030-29380-2 |
ISSN: | 1611-3349 |
Last Modified: | 26 Oct 2022 07:35 |
URI: | https://orca.cardiff.ac.uk/id/eprint/125234 |
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